Core functions as well as diagnostic and calibration tools for combining matching and linear regression for causal inference in observational studies.
|Author||Alireza S. Mahani, Mansour T.A. Sharabiani|
|Date of publication||2015-07-12 11:06:19|
|Maintainer||Alireza S. Mahani <email@example.com>|
|License||GPL (>= 2)|
lalonde: Lalonde's National Supported Work Demonstration data
lindner: Lindner Center data on 996 PCI patients analyzed by Kereiakes...
mlr: Creating a series of matched data sets with different...
mlr.bias: Treatment effect bias
mlr.bias.constructor: Generating the treatment effect bias constructor vector
mlr.combine.bias.variance: Combining bias and variance to produce total MSE for...
mlr.generate.Z.o: Generating omitted covariates from included covariates
mlr.match: Thin wrapper around 'Match' function from 'Matching' package
mlr.orthogonalize: Orthogonalization of vectors with repsect to a matrix
mlr.power: Power analysis for causal inference using linear regression
mlr.smd: Standardized mean difference
mlr.variance: Treatment effect variance
plot.summary.mlr: Plotting diagnostic and calibration objects resulting from...
summary.mlr: Applying diagnostic and calibration functions to mlr objects